This is the release note of v11.0.0a1. See here for the complete list of solved issues and merged PRs.

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Highlights

Improved NumPy functions coverage (#6078)

As series of NumPy routines have been proposed as a good-first-issue and as a result, an increasing number of contributors have sent pull requests to help increase the number of available APIs. An issue tracker with the currently implemented issues is available at #6078.

Add cupyx.scipy.special functions (#5687)

Spherical harmonics, Legendre and Gamma functions are implemented using highly performant specific CUDA kernels. Thanks to @grlee77!

Initial support for CUDA Graph API by means of stream capture API (#4567)

This PR adds the ability of using the CUDA Graph API to greatly reduce the overhead of kernel launching. This is done by using the stream capture API, and example follows.
Thanks to @leofang!

import cupy as cp

a = cp.random.randint(0, 10, 100, dtype=np.int32)
s = cp.cuda.Stream(non_blocking=True)

with s:
    s.begin_capture()
    a += 3
    a = cp.abs(a)
    g = s.end_capture()  # work is queued, but not yet launched
g.launch()
s.synchronize()

Support __device__ function in CuPy JIT (#6265)

The new interface cupyx.jit.rawkernel(device=True) is supported to define a CUDA device function.

from cupyx import jit

@jit.rawkernel(device=True)
def getitem(x, tid):
    return x[tid]

@jit.rawkernel()
def elementwise_copy(x, y):
    tid = jit.threadIdx.x + jit.blockDim.x * jit.blockIdx.x
    y[tid] = getitem(x, tid)

The following CUDA code is generated from the above python code.

__device__ int getitem_1(CArray<int, 1, true, true> x, unsigned int tid) {
  return x[tid];
}
extern "C" __global__ void elementwise_copy(CArray<int, 1, true, true> x, CArray<int, 1, true, true> y) {
  unsigned int tid;
  tid = (threadIdx.x + (blockDim.x * blockIdx.x));
  y[tid] = getitem_1(x, tid);
}

Changes

New Features

• Support stream capture (#4567)
• Add additional special functions (spherical harmonics, Legendre, Gamma functions) (#5687)
• Add cupy.asfarray (#6085)
• Add cupy.trapz (#6107)
• Add cupy.array_api.linalg (#6131)
• Add cupy.mask_indices (#6156)
• Add cupy.array_equiv API. (#6254)
• Add cupy.cublas.syrk and cupy.cublas.sbmv (#6278)
• Add cupy.vander API. (#6279)
• Add cupy.ediff1d API. (#6280)
• Add cupy.fabs API. (#6282)
• Add discrete cosine and sine transforms to cupyx.scipy.fft (#6288)
• Add logit, expit and log_expit to cupyx.scipy.special (#6300)
• Add xlogy and xlog1py to cupyx.scipy.special(#6301)
• Add tril_indices and tril_indices_from API. (#6305)
• Add cupy.format_float_positional (#6308)
• Add cupy.row_stack API. (#6312)
• Add triu_indices and triu_indices_from API. (#6316)

Enhancements

• Raise better message when importing CPU array via DLPack (#6051)
• Borrow more non-GPU APIs from NumPy (#6074)
• Add more aliases for compatibility with NumPy (#6075)
• Import more dtype aliases from NumPy (#6076)
• Borrow indexing APIs from NumPy (#6077)
• Apply upstream patch to cupy.array_api (#6086)
• Compile cub/thrust with no unique symbol (#6106)
• Support cuDNN 8.3.0 (#6108)
• Support all advanced indexing (#6127)
• Support CUDA 11.5.1 (#6166)
• Support lambda function in cupy.vectorize (#6170)
• Support eigenvalue solver 64bit API (#6178)
• Support cuTENSOR 1.4.0 (#6187)
• Make matmul support ufunc kwargs (#6195)
• Alias NumPy error classes (#6212)
• Support comparison to None and Ellipsis (#6222)
• JIT: Fix if expr typing rule (#6234)
• Support comparison with more objects (#6250)
• JIT: Support __device__ function (#6265)
• More clear warning message (#6283)
• Make streams hashable (#6285)
• Check isinstance before comparison in __eq__ (#6287)
• Support cuDNN 8.3.2 (#6314)
• Deprecate MachAr (support NumPy 1.22) (#6188)
• Fix cupy.linalg.qr to align with NumPy 1.22 (#6225)
• Change a parameter name in percentile and quantile to support NumPy 1.22 (#6228)

Performance Improvements

• Avoid 64bit division for reduce register consumption (#6019)
• Remove memory copy in matmul (#6179)

Bug Fixes

• Detect repeated axis in reduction (#5964)
• Fix __all__ in cupyx.scipy.fft (#6071)
• Fix __getitem__ on Ellipsis and advanced indexing dimension (#6081)
• Allow leading unit dimensions in copy source (#6118)
• Always test broadcast in copyto (#6121)
• Fix overloading ambiguity in ndimage filters (#6162)
• Fix empty Cholesky (#6164)
• Fix empty solve (#6167)
• Allow flip ()-shaped array (#6169)
• Handles infinities of the same sign in logaddexp and logaddexp2 (#6172)
• Fix #4675 on resolving TODO in #4198 (#6197)
• Eigenvalue solver 64bit API on CUDA 11.1 (#6201)
• Fix edge case compatibility in cupy.eye() (#6208)
• Fix linalg.eigh and linalg.eigvalsh on empty inputs (#6210)
• Fix overlapping out in matmul and (tensor)dot (#6216)
• Fix compile_with_cache returning None (#6232)
• Fixing index calculation for random constructor (#6257)
• BUG: Fix the .T attribute in the array_api namespace (#6289)
• Fix stream capture in ROCm (#6296)
• Fix cuDNN installer not working (#6337)

Code Fixes

• Remove __all__ from cupyx/scipy/* (#6149)
• Delete from os import path (#6152)
• Remove legacy cp.linalg.solve() implementation (#6161)

Documentation

• Add link to compatibility matrix (#6055)
• Update upgrade guide (#6058)
• Add v11 to compatibility matrix (#6067)
• Exclude kernel_version from comparison table (#6072)
• Doc: Add more footnotes to comparison table (#6073)
• Add polynomial modules to comparison table (#6082)
• Add CITATION.bib and update README (#6091)
• Remove LLVM_PATH note on document (#6093)
• Docs: Update linkcode implementation (#6126)
• Update footnotes in comparison table (#6142)
• Update conda-forge installation guide (#6186)
• Revise Overview for CuPy v10 (#6209)
• Docs: CentOS installation from source (#6218)
• Fix cupy.trapz docstring (#6239)
• Fix eigsh doc (#6266)
• Add cupy.positive in API Reference (#6274)

Installation

• Replace distutils with setuptools in Windows cl.exe detection (#6025)
• Fix for cuDNN directory structure in Windows (#6342)

Tests

• Fix testing.multi_gpu to add pytest marker (#6015)
• CI: add link to ROCm projects in CI coverage matrix (#6037)
• CI: use separate project for multi-GPU tests (#6050)
• Fix CI result notification message format (#6066)
• Fix CI cannot override cuSPARSELt/cuTENSOR version preinstalled (#6084)
• Workaround DeprecationWarning raised from pkg_resources (#6094)
• Fix missing multi_gpu annotation in tests (#6098)
• Fix exception handling in cupyx.distributed (#6114)
• Improve FlexCI test scripts (#6117)
• CI: Add timeout to show_config (#6120)
• Trigger FlexCI from GitHub Actions (#6130)
• CI: Fix package override sometimes fails in CentOS (#6141)
• CI: Need to update CUDA driver in cuda115.multi (#6144)
• Add tests for convolve2d (#6171)
• CI: Update limits to reduce cache size (#6174)
• CI: Fix unquoted specifiers (#6175)
• Support pre-release NumPy version in tests (#6190)
• Remove XFAIL for XPASS tests on ROCm (#6259)
• Tentatively pin to setuptools<60 in Windows CI (#6260)
• Fix cache key for github actions (#6281)
• Use NVIDIA docker images for CUDA 11.5 (#6303)
• Tentatively pin to CUDA Driver 495 (#6310)
• Remove unused dtype parameterizing in tril_indices test (#6322)
• Use get_include instead of array_equiv for fallback test (#6333)
• CI: Add cuda-slow test in FlexCI (#6335)
• CI: use CUDA docker images for CUDA Python CI (#6336)

Others

• Add doc issue template (#6294)
• Bump version to v11.0.0a1 (#6344)

Contributors

The CuPy Team would like to thank all those who contributed to this release!

@akochepasov @amanchhaparia @asi1024 @ColmTalbot @emcastillo @eternalphane @grlee77 @haesleinhuepf @khushi-411 @kmaehashi @leofang @okuta @ptim0626 @SauravMaheshkar @shwina @takagi @thomasjpfan @tom24d @toslunar @twmht @WiseroOrb @Yutaro-Sanada